User Retention & Engagement
Measuring and improving how users stick with a product after they first convert: retention rate and cohort retention curves (day 1, day 7, day 30, and longer horizons), churn rate, reactivation and resurrection of lapsed users, and engagement-depth signals such as DAU, WAU, MAU, and the DAU/MAU stickiness ratio. Covers defining and computing these metrics, including basic SQL and event-log implementations, diagnosing where and why a retention curve breaks (onboarding gaps, feature-adoption gaps, seasonal or cohort-specific effects), designing experiments and product interventions that deepen habitual usage, cohort-based lifetime value (LTV), and communicating retention findings to stakeholders. This is the post-acquisition, repeat-usage side of the user lifecycle: getting a first-time visitor through signup or first purchase is covered by the companion topic Conversion Funnel Optimization, and pure-SQL implementation depth at large scale (approximate-distinct computation, survival-curve modeling, multi-state subscription churn state machines, and standalone timezone-aware day bucketing) is covered by the companion topic Advanced SQL: Metric Monitoring, Anomaly Detection, and Data Correctness at Scale.
